Give me space and motion and I will give you a world.

R Decartes

• Biophysical materials and human-made features are dynamic, changing rapidly.
• An important instrument to study interactions between natural and human systems on the earth surface.
• An important indicator and factor to climate change.
• Significant effort has done in the development of change detection methods using remotely sensed data.

1. Data processing

• Making images comparable (Rectification, classification, interpolation, resampling)

2. Change Detection (Exploratory analysis)

• How much and where were the changes

3. Change Modeling (Empirical modeling)

• How it changed and what caused the change

4. Change Simulation (Predictive modeling)

• How it will change in future or in other scenarios?

• Successful remote sensing change detection requires careful attention to:
  • remote sensor system considerations, and
  • environmental characteristics.
• Ideally, the remotely sensed data used to perform change detection is acquired by a remote sensor system that holds the following resolutions constant: temporal, spatial (and look angle), spectral, and radiometric.
• Many processed land cover databases are available, e.g. (NLCD, NOAA C-CAP)

Temporal Resolution

• Be careful to identify the optimal change detection time period(s).

  • for instance, traffic transportation studies may require a change detection period of a few minutes.
  • You don't need daily images to study deforastration.

• Temporal resolution should be held constant during change detection, if possible.

• Images used for change detection should be acquired at comparable times.

  • for instance, minimize seasonal or tidal effects.

Image rectification

• Geometric rectification may be needed to eliminate systematic and non-systematic distortions caused by different RS platforms

• Radiometric correction may be needed to eliminate avoid radiometric distortions.

Volumne Change

• Change of certain quanities over time
• e.g. changes of NDVI (vegetation), impervious surface (urban), ice cap.

Spatial pattern Change

• Changes of spatial pattern and arrangement
• e.g. fragmentation, clustering, spatial autocorrelation.

Spatial relation change

• Change of spatial or non-spatial relation with other variables
• e.g. increasing deforastration near roads, increasing urbanization in higher elevation regions.

Transition Frequency

• Frequencies of different types of changes (Markov Chain)
• e.g. what is the most frequent land cover transition, probability of a certain type of transition

Google Earth Time Laps

• Based on time series of Landsat images
• Visually observe land cover changes over time.

https://earthengine.google.com/timelapse/

Example: Land-Cover Change in Upper Barataria Basin Estuary, Louisiana, 1972-1992: Increases in Wetland Area

Nelson et al., 2002, Land-Cover Change in Upper Barataria Basin Estuary, Louisiana, 1972-1992: Increases in Wetland Area, Environmental Management, 29(5), 716-727 pdf

UAV

Building Change Detection using Unmanned Aerial Vehicle (UAV)

UAV

Constructing and Comparing 3D building changes Captured by RGB-D camera

High resolution images (e.g. Digital Globe)

• 30m resolution in 30min frequency
• Estimate Canadian's retailing industry by 'counting' cars in supermarkets' parking lots.
• Estimate China's economy by 'counting' trucks parked in factories in southeastern China.

http://global.digitalglobe.com/interactive/30cm/

http://microsites.digitalglobe.com/30cm/

Download the assignment from https://git.io/vDRCs

Submission due on March 3